Jingkuan Song

193 papers and 6.7k indexed citations i.

About

Jingkuan Song is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Jingkuan Song has authored 193 papers receiving a total of 6.7k indexed citations (citations by other indexed papers that have themselves been cited), including 172 papers in Computer Vision and Pattern Recognition, 85 papers in Artificial Intelligence and 9 papers in Signal Processing. Recurrent topics in Jingkuan Song’s work include Advanced Image and Video Retrieval Techniques (97 papers), Multimodal Machine Learning Applications (88 papers) and Domain Adaptation and Few-Shot Learning (51 papers). Jingkuan Song is often cited by papers focused on Advanced Image and Video Retrieval Techniques (97 papers), Multimodal Machine Learning Applications (88 papers) and Domain Adaptation and Few-Shot Learning (51 papers). Jingkuan Song collaborates with scholars based in China, Australia and United States. Jingkuan Song's co-authors include Heng Tao Shen, Lianli Gao, Nicu Sebe, Xianglong Liu, Jingdong Wang, Zi Huang, Yi Yang, Xing Xu, Ting Zhang and Xiangpeng Li and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Co-authorship network of co-authors of Jingkuan Song i

Fields of papers citing papers by Jingkuan Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jingkuan Song. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jingkuan Song. The network helps show where Jingkuan Song may publish in the future.

Countries citing papers authored by Jingkuan Song

Since Specialization
Citations

This map shows the geographic impact of Jingkuan Song's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jingkuan Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jingkuan Song more than expected).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

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